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Mobile app visualizes molecules in 3D

MAY 27, 2022
Combining augmented reality, machine learning, and computational chemistry to bring molecules to life for students and researchers
Ashley Piccone headshot
Press Officer AIP
Mobile app visualizes molecules in 3D internal name

Mobile app visualizes molecules in 3D lead image

Chemistry classrooms and textbooks are often full of two-dimensional renderings of molecules, which are easy to draw but don’t capture the full three-dimensional nature of the molecule. For students, accurately visualizing molecules is crucial to understanding their structure. For researchers, the same spatial properties are directly tied to the function of biomolecules like proteins.

Sakshuwong et al. developed an open-source mobile app to visualize organic molecules in 3D. The user’s phone takes a picture of a chemical structure, then the app recognizes the molecule and renders it in augmented reality. The user can also input the name of a molecule and the app will download its structure from online databases.

“In addition to the visualization, the app explains why that molecule is important and where you can find it,” said author Umberto Raucci. “So, if you found some molecule that you don’t know, you can get some information about it.”

The app can compute chemical properties in real time and is intended to be easy to use. Augmented reality frequently requires printing out a physical marker to act as a recognizable starting point, but the tool forgoes this inconvenient step.

“Also, you can take a picture of a cup of coffee or an orange, and it will show you what molecules are in it,” said author Haley Weir. “It’s kind of gamified, like Pokémon GO but for learning about what molecules are in the world.”

This recognition currently works for a limited number of objects but could be easily extended. The group plans to enhance the app’s computational capabilities, adapt it for Android, and extend it to solid state chemistry.

Source: “Bringing chemical structures to life with augmented reality, machine learning and quantum chemistry,” by Sukolsak Sakshuwong, Hayley Weir, Umberto Raucci, and Todd J. Martinez, Journal of Chemical Physics (2022). The article can be accessed at https://doi.org/10.1063/5.0090482 .

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